Project Monitoring and Evaluation with Data Management and Analysis course

Introduction

This is a comprehensive 10 days M&E course that covers the principles and practices for results based monitoring and evaluation for the entire project life cycle. This course equips participants with skills in setting up and implementing results based monitoring and evaluation systems including M&E data management, analysis and reporting. The participants will benefit from the latest M&E thinking and practices including the results and participatory approaches. This course is designed to enable the participants become experts in monitoring and evaluating their development projects. The course covers all the key elements of a robust M&E system coupled with a practical project to illustrate the M&E concepts.

Target Participants

This course is designed for researchers, project staff, development practitioners, managers and decision makers who are responsible for project, program or organization-level M&E. The course aims to enhance the skills of professionals who need to research, supervise, manage, plan, implement, monitor and evaluate development projects.

 Course duration

10 days

Course objectives

Develop project results levels

Design a project using logical framework

Develop indicators and targets for each result level

Track performance indicators over the life of the project

Evaluation a project against the set results

Develop and implement M&E systems

Develop a comprehensive monitoring and evaluation plan

Use data analysis software (Stata/SPSS/R)

Collect data using mobile data collection tools

Carryout impact evaluation

Use GIS to analyze and share project data

Course Outline

Introduction to Results Based Project Management

Fundamentals of Results Based Management

Why is RBM important?

Results based management vs traditional projects management

RBM Lifecycle (seven phases)

Areas of focus of RBM

Fundamentals of Monitoring and Evaluation

Definition of Monitoring and Evaluation

Why Monitoring and Evaluation is important

Key principles and concepts in M&E

M&E in project lifecycle

Participatory M&E

Project Analysis

Situation Analysis

Needs Assessment

Strategy Analysis

Design of Results in Monitoring and Evaluation

Results chain approaches: Impact, outcomes, outputs and activities

Results framework

M&E causal pathway

Principles of planning, monitoring and evaluating for results

M&E Indicators

Indicators definition

Indicator metrics

Linking indicators to results

Indicator matrix

Tracking of indicators

Logical Framework Approach

LFA – Analysis and Planning phase

Design of logframe

Risk rating in logframe

Horizontal and vertical logic in logframe

Using logframe to create schedules: Activity and Budget schedules

Using logframe as a project management tool

Theory of Change

Overview of theory of change

Developing theory of change

Theory of Change vs Log Frame

Case study: Theory of change

M&E Systems

What is an M&E System?

Elements of M&E System

Steps for developing Results based M&E System

M&E Planning

Importance of an M&E Plan

Documenting M&E System in the M&E Plan

Components of an M&E Plan-Monitoring, Evaluation, Data management, Reporting

Using M&E Plan to implement M&E in a Project

M&E plan vs Performance Management Plan (PMP)

Base Survey in Results based M&E

Importance of baseline studies

Process of conducting baseline studies

Baseline study vs evaluation

Project Performance Evaluation

Process and progress evaluations

Evaluation research design

Evaluation questions

Evaluation report Dissemination

M&E Data Management

Different sources of M&E data

Qualitative data collection methods

Quantitative data collection methods

Participatory methods of data collection

Data Quality Assessment

M&E Results Use and Dissemination

Stakeholder’s information needs

Use of M&E results to improve and strengthen projects

Use of M&E Lessons learnt and Best Practices

Organization knowledge champions

M&E reporting format

M&E results communication strategies

Gender Perspective in M&E

Importance of gender in M&E

Integrating gender into program logic

Setting gender sensitive indicators

Collecting gender disaggregated data

Analyzing M&E data from a gender perspective

Appraisal of projects from a gender perspective

Data Collection Tools and Techniques

Sources of M&E data –primary and secondary

Sampling during data collection

Qualitative data collection methods

Quantitative data collection methods

Participatory data collection methods

Introduction to data triangulation

Data Quality

What is data quality?

Why data quality?

Data quality standards

Data flow and data quality

Data Quality Assessments

M&E system design for data quality

ICT in Monitoring and Evaluation

Mobile based data collection using ODK

Data visualization - info graphics and dashboards

Use of ICT tools for Real-time monitoring and evaluation

Qualitative Data Analysis

Principles of qualitative data analysis

Data preparation for qualitative analysis

Linking and integrating multiple data sets in different forms

Thematic analysis for qualitative data

Content analysis for qualitative data

Manipulation and analysis of data using NVivo

Quantitative Data Analysis – (Using SPSS/Stata)

Introduction to statistical concepts

Creating variables and data entry

Data reconstruction

Variables manipulation

Descriptive statistics

Understanding data weighting

Inferential statistics: hypothesis testing, T-test, ANOVA, regression analysis

Impact Assessment

Introduction to impact evaluation

Attribution in impact evaluation

Estimation of counterfactual

Impact evaluation methods: Double difference, Propensity score matching

GIS in M&E

Introduction to GIS in M&E

GIS analysis and mapping techniques

Data preparation for geospatial analysis

Geospatial analysis using GIS software (QGIS)